Data collecting is one of most important research techniques. For example, in constructing a housing price index, one has to make at least two important choices. The first is the choice among alternative estimation methods. The second is the choice among different data sources of house prices. The choice of the dataset has been regarded as critically important from a practical viewpoint, but has not been discussed much in the literature. International Handbook on Property Price Index from United Nation, IMF, OECD and BIS in 2013 seeks to fill this gap by comparing the distributions of prices collected at different stages of the house buying/selling process, including ⑴asking prices at which properties are initially listed in a magazine, ⑵ asking prices when an offer for a property is eventually made and the listing is removed from the magazine, ⑶ contract prices reported by realtors after mortgage approval, and ⑷ registry prices. These four prices are collected by different parties and recorded in different datasets. This paper summarizes the current state of “Data Resources for Real Estate Research in Japan”, focusing on real estate prices.

Property values depend on the volume of transactions in the market and appropriate information may decrease risks of transactions. Lower risks associated with increased participants will lead to higher prices in the market. In case of Japan’s foreclosures, the number of market participants was very small because of high risks stemming from legal procedures. The successive law amendments lowered those risks, but the remaining risks are still estimated to lower the prices of sized properties by 20 to 30％. The volume of information on seized properties provided via the internet, however, is much greater than that of ordinary ones. Therefore, not only the volume of information but also the quality of consultation by professionals are important for deceasing risks and promoting transactions in the real estate market.

This article reviews several studies that have examined the impact of collateral value of real estate on firms’investment and financing and emphasizes the importance of firm-level data employed for analysis. It first reviews two seminal studies, Gan（ 2007） for Japan and Chaney et al.（ 2012） for the United States, to point out their contributions as well as potential identification problems. It then explains that Uesugi et al. （2018） address some of these identification issues by taking advantage of exogenous shocks to real estate values caused by a natural disaster. Lastly, the article provides a few suggestions of data sources for future research.

This article defines the basic concept of land use information, enumerates its popular types in Japan, and discusses their problems. Land use information is defined as the combination of attribute information, i.e., land use classification, and location information, i.e., area division, expressed in a form for computers. It is ideal to use the spaces as units of individual land use action for location information, but their information is difficult to obtain. Therefore, approximate spaces are used. In terms of the land use classification and space, available types of land use information in Japan are examined, and the direction for the solution of their problems is proposed.

This article discusses the privately owned condominium data in Japan. The data cover comprehensive condominium characteristics and help us understand the issues and mechanism of how condominium is evaluated. This article estimates the potential amount of condominium stock using the data obtained from private companies and compares the privately owned data to the public statistics. It is found that the condominium stock obtained from the private companies approximates the stock estimated from public statistics. I further consider the issues and future perspective with the emphasis on the validity of building unit based database.

Lager availability of high-frequency and high-dimension firm-level micro data with many observation （i.e., “big data”） and developments of empirical techniques suitable for handling such data （e.g., machine learning） in recent years allow economist to conduct various empirical analyses also applicable to actual economic problems in policy design and business planning. In the contexts of prediction and causal inference, which are the two major empirical approaches to such micro data, it is further useful to combine spatial/geographical data such as location of enterprises, transaction of real estate, and development of infrastructure etc. Such joint employment of firm-level micro data and spatial/geographical data contributes to, for example, better identification of new entrants and exits from markets （esp., in the case of establishments）, expanding the dimension of firm attributes and frequency of data, and better identification of exogenous shocks to each firm.

This article reviews previous literature and existing data sources on housing purchase behavior of households. Their main interests have been twofold: （i） quantifying “household portfolio” including housing and （ii）understanding “preferences” on housing and residential environment. Through a comparison between Japan and Western countries, we discuss the future direction of academic research and data accumulation process in this filed.

Research on commercial real estate is scarcer than that on residential real estate due to data limitations. Data limitations arise from a smaller number of properties, infrequent transactions, and the limited disclosure of transaction information. This study discusses data availability in the U.S. and Japan and challenges in estimating the economic depreciation rate of Japanese commercial real estate.

The data utilised for the analyses of real estate market can be classified into two categories; revealed preference data （RP） and stated preference data （SP）. In practice, RP have been already used for wide range of analyses, including composition of real estate price and rent indices. Besides, in order to assess real estate market trend correctly, observation of such indices is sometimes inadequate, because indices tend to be distorted in specific cases. Hence it is desirable to complement RP with SP. This essay gives some empirical examples of the existing researches and literatures which deal with SP in real estate field, and the author suggests advantages of utilising SP as information resources.